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Explain the Algorithm of Probabilistic networks in Machine Learning?
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Answer / Lavi Sahu
Probabilistic networks (also known as Bayesian networks or belief networks) are a type of graphical model used for probabilistic reasoning and prediction. They consist of nodes representing variables and directed edges representing causal relationships between the variables. Each node has an associated conditional probability distribution that defines the probability of the node given its parent nodes. The algorithm involves computing joint and marginal probabilities using Bayes' rule.
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